Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method for monitoring and analyzing body sounds, the method comprising: placing at least one first detection device in contact with a body to be monitored; simultaneously detecting body sounds within, above and below a frequency range of human hearing; assessing spatial distribution of sounds using an array of sensors in the at least one first detection device; amplifying a volume of body sounds within, above and below a frequency range of human hearing and transmitting all of these simultaneously detected frequency ranges via the at least one first detection device; recording the body sounds originating from at least one body location; receiving and processing the body sounds by a hardware processor; and analyzing nonlinearity of the body sounds to determine a state of health of the body by the hardware processor.
This invention relates to a method for monitoring and analyzing body sounds to assess health conditions. The method involves placing at least one detection device in contact with a body to capture sounds from various locations. The device includes an array of sensors that detect sounds across a wide frequency range, including frequencies below, within, and above human hearing. The spatial distribution of these sounds is assessed using the sensor array, and the detected sounds are amplified and transmitted simultaneously across all frequency ranges. The sounds are recorded from specific body locations and processed by a hardware processor. The processor analyzes the nonlinearity of the body sounds to determine the health state of the body. The system enables comprehensive monitoring of internal and external body sounds, providing insights into physiological conditions that may not be detectable through conventional auditory analysis. The method leverages advanced signal processing to identify abnormalities or deviations in sound patterns, which can indicate underlying health issues. The use of multiple sensors and wide-frequency detection enhances the accuracy and diagnostic potential of the analysis.
2. The method of claim 1 , further comprising forming a baseline sound recording for the body based on the body sounds recorded.
Technical Summary: This invention relates to a method for analyzing body sounds, particularly for medical or diagnostic purposes. The method involves recording sounds produced by a body, such as heartbeats, lung sounds, or digestive noises, using one or more sensors. The recorded sounds are then processed to extract relevant acoustic features, such as frequency, amplitude, or temporal patterns, which may indicate physiological conditions or abnormalities. The method further includes establishing a baseline sound recording for the body, which serves as a reference for future comparisons. This baseline is derived from the recorded body sounds and may be used to monitor changes over time, detect deviations from normal function, or assess the effectiveness of medical interventions. The baseline recording can be updated periodically to account for natural variations in the body's acoustic profile. This approach enables early detection of health issues by identifying deviations from the established baseline, improving diagnostic accuracy and patient monitoring.
3. The method of claim 2 , further comprising taking additional body sound recordings over time.
This invention relates to a system for monitoring and analyzing body sounds, such as those produced by the cardiovascular, respiratory, or digestive systems, to detect abnormalities or changes in health status. The method involves capturing initial body sound recordings using one or more sensors placed on or near the body. These recordings are processed to extract relevant acoustic features, which are then compared against reference data or historical recordings to identify deviations that may indicate medical conditions. The system may use machine learning or signal processing techniques to enhance accuracy. The method further includes taking additional body sound recordings over time to track changes in the sound patterns, allowing for continuous health monitoring. By analyzing these temporal variations, the system can detect progressive conditions, assess treatment effectiveness, or predict potential health issues before symptoms manifest. The invention may be used in clinical settings, wearable devices, or remote monitoring systems to provide early warnings or support diagnostic decisions. The approach improves upon traditional auscultation by automating sound analysis and enabling long-term trend analysis.
4. The method of claim 3 , further comprising comparing the body sound recordings taken at different times to the baseline recording to determine differences in the body sound recordings.
This invention relates to a method for monitoring body sounds to detect changes in physiological conditions. The method involves capturing baseline body sound recordings from a subject using one or more sensors, such as microphones or accelerometers, placed on or near the body. These sensors record sounds generated by internal body functions, such as heartbeats, lung sounds, or digestive activity. The baseline recordings are stored for future reference. At subsequent times, additional body sound recordings are taken using the same or similar sensors. These new recordings are then compared to the baseline to identify any differences in the recorded sounds. The comparison step may involve analyzing frequency, amplitude, or temporal patterns in the sound data to detect deviations from the baseline. The method may also include filtering the recorded sounds to remove environmental noise or other irrelevant signals. The detected differences can indicate changes in the subject's physiological state, such as the onset of a medical condition or the progression of an existing one. This approach enables continuous or periodic monitoring of internal body sounds to assess health status without invasive procedures. The method can be applied in clinical settings, remote patient monitoring, or wearable health devices.
5. The method of claim 1 , further comprising analyzing at least one aspect of the body sounds including frequency, intensity, wave form, nonlinearity of waveform, or location of sound detected in a physiological cycle.
This invention relates to the analysis of body sounds for medical or physiological monitoring. The method involves detecting and analyzing body sounds, such as those produced by the heart, lungs, or other organs, to assess physiological conditions. The analysis includes examining at least one aspect of the body sounds, such as frequency, intensity, waveform, nonlinearity of the waveform, or the location of the sound within a physiological cycle. By evaluating these characteristics, the method aims to provide insights into the health or function of the body part producing the sounds. The analysis may involve comparing the detected sounds to reference data or thresholds to identify abnormalities or changes in physiological states. This approach can be used for diagnostic purposes, monitoring disease progression, or assessing treatment effectiveness. The method may be applied in clinical settings, wearable devices, or remote monitoring systems to enhance patient care and early detection of health issues.
6. The method of claim 5 , further comprising combining results from the analysis with other health data points of the body being monitored.
This invention relates to health monitoring systems that analyze physiological data to provide insights into a user's health status. The core problem addressed is the need to integrate multiple health data points from different sources to generate a comprehensive assessment of a person's well-being. Traditional health monitoring systems often analyze data in isolation, leading to incomplete or fragmented health insights. The invention describes a method for enhancing health monitoring by combining results from an analysis of physiological data with additional health data points collected from the body being monitored. The physiological data may include measurements such as heart rate, blood pressure, oxygen saturation, or other vital signs. The analysis of this data may involve detecting patterns, anomalies, or trends that indicate potential health issues. The additional health data points may come from wearable devices, medical sensors, or other monitoring systems and could include factors like activity levels, sleep quality, dietary intake, or environmental conditions. By integrating these diverse data sources, the method provides a more holistic view of the user's health. The combined analysis may improve the accuracy of health assessments, enable early detection of health risks, and support personalized health recommendations. The system may also adapt over time by learning from the user's data to refine its predictions and insights. This approach is particularly useful in preventive healthcare, chronic disease management, and fitness tracking.
7. The method of claim 6 , further comprising analyzing the combined results by deep learning and artificial intelligence.
Technical Summary: This invention relates to data processing systems that combine and analyze results using deep learning and artificial intelligence. The method involves integrating multiple data sources or processing steps to generate combined results, which are then subjected to advanced analytical techniques. The deep learning and artificial intelligence components are used to extract meaningful patterns, insights, or predictions from the combined data. This approach enhances decision-making by leveraging automated, data-driven analysis. The invention is particularly useful in fields where large datasets or complex relationships need to be interpreted, such as healthcare diagnostics, financial forecasting, or industrial automation. By applying deep learning and AI to the combined results, the system can identify correlations, anomalies, or trends that may not be apparent through traditional analysis methods. The method improves accuracy, efficiency, and scalability in data interpretation, making it suitable for real-time or high-volume applications. The use of AI ensures adaptability to new data patterns, while deep learning models can handle unstructured or high-dimensional data effectively. This technique addresses the challenge of deriving actionable insights from diverse or noisy datasets, providing a robust solution for modern data-intensive industries.
8. The method of claim 1 , wherein a second detection device is placed on the body being monitored at a location separate from the at least one first detection device.
A system and method for monitoring physiological parameters of a subject using multiple detection devices. The technology addresses the challenge of accurately measuring physiological signals, such as heart rate or blood pressure, in real-time while minimizing interference from motion or environmental noise. The invention involves placing at least one primary detection device on the subject's body to capture physiological data, such as electrical signals from the heart or blood flow dynamics. A secondary detection device is positioned at a distinct location on the body to provide additional data points, improving signal accuracy and reliability. The secondary device may operate independently or in conjunction with the primary device, allowing for cross-verification of measurements. The system processes the combined data to enhance signal clarity, reduce artifacts, and provide more precise physiological readings. This approach is particularly useful in medical monitoring, fitness tracking, or wearable health devices where accurate and continuous data collection is essential. The use of multiple detection points helps mitigate errors caused by movement, sensor misplacement, or external interference, ensuring more reliable health assessments.
9. A system for analyzing sounds generated by an animal's body, comprising: at least one first detection device for simultaneous auscultation of internal sounds from the animal's body wherein the auscultated sounds are within, above and below human hearing range and transmitting all of these simultaneously detected frequency ranges, wherein the first detection device is in wireless communication with a receiver; wherein the receiver receives the auscultated internal sounds from the first detection device; a processor, in communication with the receiver, for generating audio and video output formed from the internal sounds auscultated by the first detection device; a monitor for displaying the audio and video output from the processor; and further comprising wherein the processor is configured to analyze nonlinearity of the body sounds and associating same with a health status of the body.
This system analyzes sounds generated by an animal's body to assess health status. The system includes at least one detection device that performs simultaneous auscultation of internal body sounds across a wide frequency range, including frequencies below, within, and above human hearing range. The detection device wirelessly transmits all detected frequencies to a receiver. A processor connected to the receiver generates audio and video outputs from the auscultated sounds, which are displayed on a monitor. The processor also analyzes the nonlinearity of the body sounds and correlates these characteristics with the animal's health status. The system enables comprehensive monitoring of internal sounds, providing insights into physiological conditions that may not be detectable through conventional auscultation methods. By capturing and analyzing a broader spectrum of frequencies, the system enhances diagnostic capabilities, particularly for detecting subtle or abnormal sound patterns associated with various health conditions. The integration of audio and video outputs allows for real-time visualization and assessment of the animal's internal sounds, supporting more accurate and timely medical evaluations.
10. The system of claim 9 , wherein the processor communicates with at least one communication system other than the monitor.
A system for monitoring and communicating data in a networked environment addresses the need for efficient and reliable data exchange between multiple devices. The system includes a processor that processes data from a monitor, which may be a sensor or a monitoring device collecting real-time information such as environmental conditions, system performance, or operational status. The processor is configured to analyze and transmit this data to other components within the system. A key feature is the processor's ability to communicate with at least one additional communication system beyond the monitor, enabling broader data distribution or integration with external networks. This secondary communication system may include wireless or wired networks, cloud-based platforms, or other interconnected devices, allowing for enhanced data sharing, remote access, or system-wide coordination. The system ensures seamless data flow and interoperability, improving monitoring accuracy and responsiveness in applications such as industrial automation, healthcare, or smart infrastructure. By supporting multiple communication channels, the system provides flexibility in deployment and scalability for diverse monitoring and control scenarios.
11. The system of claim 9 , wherein a peripheral margin is slightly offset from a middle portion of a surface of the first detection device.
Technical Summary: This invention relates to a system for detecting objects or conditions using a detection device with a specific structural configuration. The system addresses the challenge of accurately detecting objects or conditions while minimizing interference from peripheral factors. The detection device includes a surface with a middle portion and a peripheral margin. The peripheral margin is slightly offset from the middle portion, creating a distinct spatial relationship between these two regions. This offset design helps isolate the detection area, reducing noise or interference from surrounding elements. The middle portion serves as the primary detection zone, while the peripheral margin acts as a buffer or guard region. The offset ensures that the detection process remains focused on the intended area, improving accuracy and reliability. The system may be used in various applications, such as sensors, imaging devices, or measurement tools, where precise detection is critical. The offset margin design enhances performance by minimizing edge effects and external disturbances.
12. The system of claim 11 , wherein an adhesive is placed in the offset peripheral margin to affix a recording disk to the body surface to improve quality of recording of the body sounds and decrease external noise.
This invention relates to a system for recording body sounds, such as heart or lung sounds, with improved signal quality and reduced external noise. The system includes a body surface-mounted device with a recording disk that captures acoustic signals from the body. A key feature is an offset peripheral margin around the recording disk, which is filled with an adhesive. The adhesive serves two purposes: it secures the recording disk to the body surface, ensuring stable contact and minimizing movement artifacts, and it forms a seal that blocks external noise from interfering with the recorded body sounds. By improving the coupling between the recording disk and the body, the adhesive enhances the fidelity of the recorded signals while attenuating unwanted environmental noise. This design is particularly useful in medical applications where accurate and clear body sound recordings are critical for diagnosis. The adhesive may be applied in a controlled manner to ensure optimal performance without compromising patient comfort or mobility. The system may also include additional components, such as signal processing units or wireless transmission modules, to further enhance functionality. The overall goal is to provide a reliable, high-quality recording solution for body sounds in clinical or remote monitoring settings.
13. The system of claim 9 , wherein the system forms a baseline sound recording for a body based on the body sounds recorded.
This invention relates to a system for analyzing body sounds, such as those produced by internal organs or physiological processes, to monitor health conditions. The system records sounds from a body, processes the recorded sounds to extract relevant acoustic features, and compares them to a baseline sound recording to detect anomalies or changes over time. The baseline recording is generated from previously recorded body sounds, serving as a reference for normal physiological activity. By continuously or periodically comparing new recordings to this baseline, the system can identify deviations that may indicate medical issues, such as irregular heartbeats, respiratory abnormalities, or other conditions. The system may include sensors, signal processing components, and analysis algorithms to enhance the accuracy of sound detection and comparison. The baseline recording can be updated dynamically to account for natural variations in body sounds, ensuring reliable monitoring over extended periods. This approach enables early detection of health issues through non-invasive sound analysis, reducing the need for invasive diagnostic procedures.
14. The system of claim 9 , wherein the system analyzes at least one aspect of the body sounds such as frequency, intensity, wave form, nonlinearity of waveform, or location of sound detected in a physiological cycle.
This invention relates to a system for analyzing body sounds to monitor physiological conditions. The system detects and processes sounds generated by the body, such as those from the cardiovascular, respiratory, or digestive systems, to assess health status. The system includes sensors to capture body sounds and a processing unit that evaluates specific acoustic characteristics. These characteristics include frequency, intensity, waveform shape, nonlinearity of the waveform, and the location of sound detection within a physiological cycle. By analyzing these aspects, the system can identify abnormalities or changes in physiological function, such as irregular heartbeats, respiratory distress, or digestive issues. The system may also correlate sound data with other physiological measurements to provide a comprehensive health assessment. The analysis helps in early detection of medical conditions, enabling timely intervention. The system is designed to be non-invasive and suitable for continuous or periodic monitoring in clinical or home settings. The technology aims to improve diagnostic accuracy and patient care by leveraging advanced sound analysis techniques.
15. The system of claim 9 , wherein a second detection device is placed on the animal's body being monitored at a location separate from the at least one first detection device.
This invention relates to a monitoring system for animals, specifically designed to track physiological or behavioral data from multiple locations on an animal's body. The system addresses the challenge of obtaining comprehensive health or activity data by using multiple detection devices placed at different positions on the animal. A primary detection device is positioned on the animal to collect initial data, while a secondary detection device is placed at a separate location to provide additional or complementary measurements. The secondary device may detect different parameters or confirm readings from the primary device, improving accuracy and reliability. The system may be used for veterinary monitoring, research, or animal welfare applications, where continuous or periodic data collection from multiple body locations is beneficial. The devices may communicate wirelessly or via wired connections to a central processing unit for data aggregation and analysis. This setup ensures that critical health indicators or behavioral patterns are captured from multiple perspectives, reducing the risk of missed or inaccurate readings. The system is adaptable to various animal species and can be customized based on the specific monitoring needs, such as heart rate, movement, or environmental exposure tracking.
Unknown
February 4, 2020
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